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BSMA3012 - Linear Statistical Models

346 words
2 min read
FieldValue
Course CodeBSMA3012
LevelDegree Level Course
Credits4
TypeElective
Pre-requisitesNone

📖 Description

To introduce linear statistical models and their applications in estimation and testing. The course will illustrate concepts with specific examples, data sets and numerical exercises using statistical package R.

🗓️ Weekly Syllabus

WeekTopic
Week 1Review of Estimation, Hypothesis Testing
Week 2Review of working with R-package
Week 3Least square estimation, estimable linear functions
Week 4Normal equations
Week 5Best Linear Unbiased Estimates (BLUEs).
Week 6Gauss-Markov Theorem.
Week 7Degrees of freedom. Fundamental Theorems of Least Square.
Week 8Testing of linear hypotheses.
Week 9One-way and two-way classification models
Week 10ANOVA and ANCOVA.
Week 11Nested models. Multiple comparisons
Week 12Introduction to random effect models.

📚 Books & Resources

Prescribed Books The following are the suggested books for the course:
        Plane Answers to Complex Questions The Theory of Linear Models, Springer by R. Christensen.
        
        Linear Statistical Inference by C. R. Rao.

📝 About the Instructors

Siva Athreya
Professor,
International Centre for Theoretical Sciences - TIFR and Indian Statistical Institute,
Bangalore Centre
Siva Athreya received his Bachelor of Science (Honours) Mathematics from St. Stephen’s College, New Delhi, India in 1991. After obtaining a Master of Statistics from Indian Statistical Institute,  Kolkata, India in 1993 he obtained his PhD in Mathematics from the University of Washington, Seattle, U.S.A. in 1998. His research interests include: Stochastic Analysis (Stochastic Partial Differential Equations and Stochastic Differential Equations); Random walks among mobile traps; Random Graphs; Tree-valued Processes; Computational Epidemiology. He currently serves as Editor-in-Chief: Electronic Communications in Probability.
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